dwarka, rm, maree, ff, esterhuysen, jj, botha, b, mtshali, n arc, … · 2013. 3. 7. · dwarka,...
TRANSCRIPT
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A better understanding of the behaviour of different topotypes of Foot-and-Mouth Disease Viruses
circulating in the domestic and wildlife populations.
Dwarka, RM, Maree, FF, Esterhuysen, JJ, Botha, B, Mtshali, N
ARC, Onderstepoort Veterinary Institute, Transboundary Animal Diseases Programme
Pool 2 O, A, Asia 1
Pool 1 O, A, Asia 1
Pool 3 O, A, Asia 1
The conjectured status of FMD showing approximate distribution of regional virus pools.
Pool 7 O, A
Pool 5 O, A, SAT 1, 2
Pool 4 A, O, SAT 1, 2, 3 Pool 6
SAT 1, 2, 3
Intermediate, sporadic
Endemic
Free
Free. Virus present in game parks
Free with vaccination
Countries with multiples zones: FMD-free, free with vaccination or not free
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• In Africa, FMD is widespread throughout the continent
• Six of the seven serotypes occur on the continent
• Only serotype Asia 1 not recorded
• Different ‘patterns’ of disease occur
Vosloo et al., 2002
Map of typed FMD outbreaks in Africa
• FMD epidemiology is complex on the African continent
• Serotype distribution differs between geographic regions
• Wildlife are involved in certain regions
• Intratypic variants occur within serotypes
Foot-and-mouth disease within pools 4, 5, 6 in Africa
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Molecular epidemiology of FMD in Africa
• The genes encoding the structural proteins are used to determine phylogenetic relationships
cccccc
ORF 5’ 3’ UTR UTR
poly A L 1A 1B, 1C, 1D P2 P3
Structural proteins Non-structural proteins
1D: outer capsid coding gene used for initial phylogenetic analysis P1: - Resolve the phylogeny obtained with the 1D gene sequencing
- Greater depth in sequencing information covering the antigenic region of the capsid
- Strains can be selected for vaccine matching studies and structural studies using mathematically modelling Genome length sequencing: Recombination of virus populations
can be studied between/within serotypes
Gene Regions used for sequencing
cccccc
ORF 5’ 3’ UTR UTR
poly A L 1A 1B, 1C, 1D P2 P3
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Definition of genotypes: group or cluster of closely related viruses When a number of genotypes cluster/group together in a particular geographic location we term this a topotype
Common factors for all serotypes KNP/9/03/Ribye-Waterhole
KNP/1/06/2/Masakosa KNP/06/03/Shangoni SAR/2/04/Selwana-farm
SAR/15/04/Dzumeri SAR/11/01/Craigieburn
KNP/31/95 KNP/07/88 KNP/19/89 KNP/32/92/Boyela
KNP/5/91/Satara SAR/1/03/Masisi
ZIM/08/94 MAL/01/03
MAL/1/08 ZIM/12/02/Chipinge
ZIM/13/02/Chipinge ZIM/6/03/Harare ZIM/4/03/Harare ZIM/7/03/Chinhoyi
MAL/3/75 MAL/01/04/Malawi
ZAM/9/93 ZAM/10/93
ZAM/7/96 BOT/31/98/Vumbura NAM/4/07/Caprivi SWA/4/89
ZIM/10/02/Bikita ZIM/01/01/Bulawayo
ZIM/01/02/Beitbridge BOT/13/02
BOT/4/06/2 BOT/5/06/2
ZIM/34/90 ZIM/267/98/Chizarira
ZIM/7/95/Sengwa NAM/01/92
08/467/Kavango/Namibia BOT/18/98
BOT/1/98/Nxaraga NAM/286/98
ZIM/08/02/Lupane ZIM/07/83/Nyamandlovu
ZIM/4/88 ZIM/42/97
ZIM/48/97 SAU4/00
93 92 99
100
100
100
100
92
100 98
100
99
100
100
92
100
100
100
100
89
81 99
95
87
92
78 100
98 100
78
78
84
61 65
0.05
I
III
II
Database of FMD isolates from buffalo in the KNP KNP/9/03/Ribye-Waterhole
KNP/1/06/2/Masakosa KNP/06/03/Shangoni SAR/2/04/Selwana-farm
SAR/15/04/Dzumeri SAR/11/01/Craigieburn
KNP/31/95 KNP/07/88 KNP/19/89 KNP/32/92/Boyela
KNP/5/91/Satara SAR/1/03/Masisi
ZIM/08/94 MAL/01/03
MAL/1/08 ZIM/12/02/Chipinge
ZIM/13/02/Chipinge ZIM/6/03/Harare ZIM/4/03/Harare ZIM/7/03/Chinhoyi
MAL/3/75 MAL/01/04/Malawi
ZAM/9/93 ZAM/10/93
ZAM/7/96 BOT/31/98/Vumbura NAM/4/07/Caprivi SWA/4/89
ZIM/10/02/Bikita ZIM/01/01/Bulawayo
ZIM/01/02/Beitbridge BOT/13/02
BOT/4/06/2 BOT/5/06/2
ZIM/34/90 ZIM/267/98/Chizarira
ZIM/7/95/Sengwa NAM/01/92
08/467/Kavango/Namibia BOT/18/98
BOT/1/98/Nxaraga NAM/286/98
ZIM/08/02/Lupane ZIM/07/83/Nyamandlovu
ZIM/4/88 ZIM/42/97
ZIM/48/97 SAU4/00
93 92 99
100
100
100
100
92
100 98
100
99
100
100
92
100
100
100
100
89
81 99
95
87
92
78 100
98 100
78
78
84
61 65
0.05
5
SAT - 1 KNP/3/07 Dzombo KNP/5/07 Dzombo KNP/10/07 Bububu KNP/19/07 Langtoon Dam KNP/21/07 Langtoon Dam
SAT - 2 KNP/4/07 Dzombo KNP/11/07 Bububu KNP/20/07 Langtoon Dam KNP/25/07 Boyela
SAT -3 KNP/2/07 Dzombo KNP/26/07 Boyela
Limpopo river
Pafuri Levuvhu river
Olifants river
Punda Maria
Mopani
Shingwedzi
Olifants
Letaba
Phalaborwa
Shingwedzi river
KNP NORTH
Mphongolo
Bububu
Langtoon dam
Boyela
Dzombo Bakoor Shigumane
Ø DZOMBO – SAT-1, SAT-2 & SAT-3 Ø LANGTOON DAM – SAT-1 & SAT-2 Ø BUBUBA – SAT-1 & SAT-2 Ø BOYELA – SAT-2 & SAT-3
KNP isolates updated
SAT -1 Letaba isolates -Eight cluster within
the southern topotype but in four different genotypes
Isolates cluster within the Southern topotype, but in four different genotypes.
Limpopo river Pafuri Levuvhu river
Olifants river
Tim
bava
ti riv
er
Punda Maria
Mopani
Shingwedzi
Olifants Letaba
Satara Klaserie PNR
Sabie Sabie PNR
Timbavati PNR Orpen
Lower Sabie
Crocodile river
Skukuza
Pretoriuskop
Malelane
Shingwedzi river
Crocodile Bridge
Mbyamiti river
KNP/2/06/Maseya KNP/3/06/Maseya
KNP/2/02/Elandskuil KNP/26/08
KNP/893/98/Shipane W/M KNP/35/92/SHINGWEDZI
KNP/6/06/Makwadsi 10/1364/Zidlele DT 10/1693/Feedlot GP
KNP/8/95/MONDSWENI KNP/7/03/Shangoni
KNP/1584/98/Baranukee KNP/8/08 KNP/14/08 KNP/10/07/Bububu KNP/3/07/Dzombo KNP/8/07/Dzombiene
SAR/9/81 GN13/91 KNP/01/01/Shipandi-W/M
SAR/7/03/buffalo SAR/6/03/buffalo
SAR/1/00/Phalaborwa KNP20/89/KWA-MFAMEBTO
SAR/2/10/Phalaborwa SAR/8/10/Gravelotte
KNP/397/98/RIETPAN KNP/400/98/RIETPAN
KNP/22/08 KNP/24/08
KNP/17/96 SAR/08/02/Mauricedale
KNP/21/07/Langtoon Dam KNP/15/08 KNP/11/03/Masorini KNP/18/08 KNP/17/08
ZIM/05/99 SAR/1/09/Makoko DT KNP/5/05 KNP/148/91
53
81
79
99
73 100
100 97
66
100
100 100
100
99
90
100
Phylogenetic analysis SAT 1 KNP viruses
SAT-1 (2008)
I I
II
III
IV
KNP
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South Africa: Wildlife/ cattle interface
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Genetic variability of FMDV based on P1 sequencing
SAR1
/200
9
SA
R2/2
009
SA
R4
/20
09
SA
R3/2
009
SAR7
/200
9
SAR5/2009SAR6/2009KNP/196/91/1
KNP/148/91/1SAR/09/81/1KNP/41/95/1ZIM/HV/03/90
ZIM/GN/13/90
ZIM/25/90/1
MOZ/03/02/1
ZAM/02/93/1
TAN/37/99/1
KEN/05/98/1
ZIM/06/94/1
NAM/307/98/1
BOT/3/06/1
UG
A/03/99/1U
GA
/01/97/1N
IG/05/81/1
SU
D/0
3/7
6/1
NIG
/08/76/1N
IG/1
5/7
5/1
NIG
/06/7
6/1
SE
N/0
7/8
3/2
RW
A/0
2/0
1/2
ZA
I/01/7
4/2
UG
A/0
2/0
2/2
KE
N/0
3/5
7/2
SA
U/0
6/0
0/2
ER
I/12/
89/2
GH
A/08
/91/
2
SEN
/05/75
/2
ANG/04
/74/2
ZIM
/14/90
/2
ZIM/17
/91/2
ZIM/34/90/2
BOT/4/06/2
ZIM/07/83/2
ZIM/01/88/2
ZAM/07/96/2 RHO/01/48/2 KEN/08/99/2
ZIM/08/94/2 ZIM/GN/10/91
SAR/16/83/2
KNP/51/93/2
KN
P/02/89/2
KN
P/1
9/8
9/2
UGA/02/97/3
ZAM/04/96/3
BE
C/16/53/3
KN
P/1
0/9
0/3
ZIM
/05/9
1/3
A22
A1
2 O1
Ka
uf
O1T
ai
0.05
SAT1
SAT3
SAT2
Type A Type O
Neighbour-joining tree depicting the relationships between nucleotide sequences of the P1 regions of 5 FMDV serotypes
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KNP/148/91 [Buffalo]
KNP/ 41/95 [Buffalo]
ZIM/6/94 [Buffalo]
NAM/307/98 [Buffalo]
MOZ/3/02 [Bovine]
KEN/05/98 [Bovine]
UGA/1/97 [Buffalo]
NIG 8/76 [Bovine]
BHK-21 IB-RS2 CHO SAT1
Southern Africa
East Africa West Africa
Plaque morphology assists as a measurement of adaptation to BHK cells
Peninah Nsamba, Belinda. Blignaut and Francois. F. Maree TADP, OVI and University of Pretoria
SAT1 Plaque Phenotypes in different cell lines
SAT2 Plaque Phenotypes in different cell lines
SAT2/KNP 2/89 [Impala]
SAT2/KNP 51/93 [Impala]
SAT2/ZIM 1/88 [Buffalo]
SAT2/ANG/4/74 [Bovine]
SAT2/UGA/2/02 [Bovine]
SAT2/RWA/2/01 [Bovine]
SAT2/SEN/7/83 [Bovine]
SAT2/GHA/8/91 [Bovine]
BHK-21 IB-RS2 CHO SAT2
East Africa
West Africa
Southern Africa
Passage History of virus isolates - PK or BTY – 1-2 times - IB-RS – 3-4 times
Peninah Nsamba, Belinda. Blignaut and Francois. F. Maree TADP, OVI and University of Pretoria
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Pool 6
Topotype 1
Topotype 3
Topotype 2
SAR/2/09
SAR/4/09
SAR/1/09
SAR/3/09
SAR/7/09
SAR/5/09
SAR/6/09
KNP/196/91
KNP/148/91
KNP/11/03
SAR/8/02
SAR/9/03
SAR/33/00
KNP/41/95
SAR/7/03
KNP/07/03
KNP/10/03
ZIM/HV/03/90
ZIM/GN/13/90
SAR/09/81
KEN/05/98
TAN/37/99
ZAM/01/06
ZAM/02/93
ZIM/03/95
ZIM/14/98
ZIM/25/90
ZIM/11/03
MOZ/01/02
MOZ/03/02
BOT/01/06
BOT/03/06
NAM/01/10
ZIM/03/03
ZIM/06/94
NAM/272/98
BOT/02/98
NAM/307/98
NAM/308/98
UGA/01/97
UGA/03/99
100
99100
99
92
100
69
98
51
86
100
98
100
67
100
77
100
98
100
81
100
100
8384
88
64
100
95
66
69
53
65
100
41
26
72
23
0.05
Vaccine matching studies
Antigenic variation (r values)
• r-value = heterologous neutralising titer / homologous titer
• r-value range: 0.4-1.0: good cross-protection against outbreak strain 0.2-0.4: reasonable cross-protection; a potent vaccine will still protect against outbreak virus 0-0.2: poor/no cross-protection
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Topotype 1 Topotype 2 Topotype 3
ZAM/1/06 SAR/9/81 BOT/1/06 KNP/196/91
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
r-value criteria
SAT2 vaccine strains
SAT2 reference viruses
Per
cent
age
viru
ses
in e
ach
cate
gory
SAT2 antigenic variation
Vaccine match based on r-values
11
Fig. 2; Maree et al.
A B
SAT1/SAR/9/81 SAT2/ZIM/7/83
Structural models of FMDV
Capsid structures of SAT 1 and SAT 2. Variation in surface exposed regions. Study of correlation between the field isolates and vaccines
SAT-1:
Topotype I
Topotype IITopotype III
Topotype IV
Topotype V
Topotype VITopotype VII
Topotype VIII
MORROCCO
MAURITANIA
ALGERIA
GHANA
MALI
GUINEAGUINEA-BISAU
SIERRA-LEONE
LIBERIA
BURKINAFASO
GAMBIA
TOGOBENIN
NIGERIA
NIGER
EGYPT
SOMALIA
LYBIA
CHAD
SUDAN
CAMEROON
CENTRALAFRICANREPUBLIC
ETHIOPIA
EQUATORIALGUINEA UGANDA
RWANDA
TANZANIA
ZAIREGABONCONGO
ANGOLA
NAMIBIA
ZAMBIA
ZIMBABWE
BOTSWANA
SWAZILAND
LESOTHOSOUTHAFRICA
TUNISIA
KENYA
COTED’IVOIRE
SENEGAL
ERITREA
YEMEN
SAUDI ARABIA
ISRAELJORDAN
BURUNDI
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SAT-2:
Topotype I
Topotype IITopotype III
Topotype IV
Topotype V
Topotype VITopotype VII
Topotype VIIITopotype IX
Topotype XIVTopotype XIIITopotype XII
Topotype XITopotype X
MORROCCO
MAURITANIA
ALGERIA
GHANA
MALI
GUINEA GUINEA- BISAU
SIERRA- LEONE
LIBERIA
BURKINA FASO
GAMBIA TOGO
B E N I N
NIGERIA
NIGER
EGYPT
SOMALIA
LYBIA
CHAD SUDAN
CAMEROON CENTRAL AFRICAN REPUBLIC
ETHIOPIA
EQUATORIAL GUINEA UGANDA
RWANDA
TANZANIA
ZAIRE GABON CONGO
ANGOLA
NAMIBIA
ZAMBIA ZIMBABWE
BOTSWANA SWAZILAND
LESOTHO SOUTH AFRICA
TUNISIA
KENYA
COTE D’IVOIRE
SENEGAL
ERITREA YEMEN
SAUDI ARABIA
ISRAEL JORDAN
BURUNDI
Buffalo/cattle sampling in SADC countries during 2010-2012:
• Malawi • Tanzania • Zambia • Mozambique • Angola
Regional Activities SADC TADs Project
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Concluding remarks • A comprehensive database of FMD viruses and
sequences from SADC countries enables a better understanding on the evolution of the virus.
• When a FMD virus database is represented by diverse topotypes, it enables diagnosticians to better understand and trace the possible origins of outbreak strains.
• Understanding the possible source of an outbreak could play a role in the immediate control strategy for that region. It also enables scientists to assess if a particular topotype is dominant in a region, which could have an impact on vaccine strain selection for that area.
Concluding remarks • If vaccination is applied as a control measure, a
topotype rich database of viruses will enable better vaccine matching studies to be performed to evaluate the most appropriate vaccine strain.
• Scientists can study the relationships between FMD viruses from different topotypes and perform vaccine matching studies across topotypes,
• However, for a holistic regional control strategy, concerted collaborative efforts between governments, industry, farmers and research institutions are central to effectively mitigating the risk posed by a disease such as FMD.
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Thank You